MLS-C01 Practice Question: Machine Learning Implementation and Operations
A team uses AWS Glue ETL jobs to preprocess data for SageMaker training. The job runs successfully but the output data is empty. What is the most likely cause?
⚠ Common exam trap
Test-takers frequently assume empty output must be caused by a failure or resource issue (like memory or partitioning), rather than a logical error in the transformation logic that silently removes all data.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The filter transformation condition is too restrictive, removing all rows
A filter transformation in AWS Glue ETL jobs can remove all rows if the condition is too restrictive, resulting in an empty output dataset. This is a common logic error where the filter predicate (e.g., `df.filter("value > 100")`) matches no records, causing the DynamicFrame to be empty after transformation. The job succeeds because no runtime error occurs, but the output is empty.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
There is a data type mismatch between source and target
Why it's wrong here
This would cause errors, not empty output.
- ✗
The source data is partitioned and only a subset of partitions is read
Why it's wrong here
Partition pruning reads only relevant partitions, but data should still exist.
- ✓
The filter transformation condition is too restrictive, removing all rows
Why this is correct
Filtering all rows results in empty output.
- ✗
The Glue job runs out of memory and fails silently
Why it's wrong here
Out of memory causes job failure, not empty output.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.